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JournalISSN: 0923-5965

Signal Processing-image Communication 

Elsevier BV
About: Signal Processing-image Communication is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Image processing & Image quality. It has an ISSN identifier of 0923-5965. Over the lifetime, 2736 publications have been published receiving 68120 citations.


Papers
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Journal ArticleDOI
TL;DR: A new philosophy in designing image and video quality metrics is followed, which uses structural dis- tortion as an estimate of perceived visual distortion as part of full-reference (FR) video quality assessment.
Abstract: Objective image and video quality measures play important roles in a variety of image and video pro- cessing applications, such as compression, communication, printing, analysis, registration, restoration, enhancement and watermarking. Most proposed quality assessment ap- proaches in the literature are error sensitivity-based meth- ods. In this paper, we follow a new philosophy in designing image and video quality metrics, which uses structural dis- tortion as an estimate of perceived visual distortion. A com- putationally ecient approach is developed for full-reference (FR) video quality assessment. The algorithm is tested on the video quality experts group (VQEG) Phase I FR-TV test data set. Keywords—Image quality assessment, video quality assess- ment, human visual system, error sensitivity, structural dis- tortion, video quality experts group (VQEG)

1,083 citations

Journal ArticleDOI
TL;DR: This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics, and methodology for determining drawbacks of existing visual quality metrics is described.
Abstract: This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics. With respect to TID2008, the new database contains a larger number (3000) of test images obtained from 25 reference images, 24 types of distortions for each reference image, and 5 levels for each type of distortion. Motivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented. Mean opinion scores (MOS) for the new database have been collected by performing 985 subjective experiments with volunteers (observers) from five countries (Finland, France, Italy, Ukraine, and USA). The availability of MOS allows the use of the designed database as a fundamental tool for assessing the effectiveness of visual quality. Furthermore, existing visual quality metrics have been tested with the proposed database and the collected results have been analyzed using rank order correlation coefficients between MOS and considered metrics. These correlation indices have been obtained both considering the full set of distorted images and specific image subsets, for highlighting advantages and drawbacks of existing, state of the art, quality metrics. Approaches to thorough performance analysis for a given metric are presented to detect practical situations or distortion types for which this metric is not adequate enough to human perception. The created image database and the collected MOS values are freely available for downloading and utilization for scientific purposes. We have created a new large database.This database contains larger number of distorted images and distortion types.MOS values for all images are obtained and provided.Analysis of correlation between MOS and a wide set of existing metrics is carried out.Methodology for determining drawbacks of existing visual quality metrics is described.

943 citations

Journal ArticleDOI
TL;DR: It is found that SSEQ matches well with human subjective opinions of image quality, and is statistically superior to the full-reference IQA algorithm SSIM and several top-performing NR IQA methods: BIQI, DIIVINE, and BLIINDS-II.
Abstract: We develop an efficient general-purpose no-reference (NR) image quality assessment (IQA) model that utilizes local spatial and spectral entropy features on distorted images. Using a 2-stage framework of distortion classification followed by quality assessment, we utilize a support vector machine (SVM) to train an image distortion and quality prediction engine. The resulting algorithm, dubbed Spatial–Spectral Entropy-based Quality (SSEQ) index, is capable of assessing the quality of a distorted image across multiple distortion categories. We explain the entropy features used and their relevance to perception and thoroughly evaluate the algorithm on the LIVE IQA database. We find that SSEQ matches well with human subjective opinions of image quality, and is statistically superior to the full-reference (FR) IQA algorithm SSIM and several top-performing NR IQA methods: BIQI, DIIVINE, and BLIINDS-II. SSEQ has a considerably low complexity. We also tested SSEQ on the TID2008 database to ascertain whether it has performance that is database independent.

562 citations

Journal ArticleDOI
TL;DR: A generic Fourier descriptor (GFD) is proposed to overcome the drawbacks of existing shape representation techniques by applying two-dimensional Fourier transform on a polar-raster sampled shape image.
Abstract: Shape description is one of the key parts of image content description for image retrieval. Most of the existing shape descriptors are usually either application dependent or non-robust, making them undesirable for generic shape description. In this paper, a generic Fourier descriptor (GFD) is proposed to overcome the drawbacks of existing shape representation techniques. The proposed shape descriptor is derived by applying two-dimensional Fourier transform on a polar-raster sampled shape image. The acquired shape descriptor is application independent and robust. Experimental results show that the proposed GFD outperforms common contour-based and region-based shape descriptors.

534 citations

Journal ArticleDOI
TL;DR: Although the JPEG 2000 standard only specifies the decoder and the codesteam syntax, the discussion will span both encoder and decoder issues to provide a better understanding of the standard in various applications.
Abstract: In 1996, the JPEG committee began to investigate possibilities for a new still image compression standard to serve current and future applications. This initiative, which was named JPEG 2000, has resulted in a comprehensive standard (ISO 15444∣ITU-T Recommendation T.800) that is being issued in six parts. Part 1, in the same vein as the JPEG baseline system, is aimed at minimal complexity and maximal interchange and was issued as an International Standard at the end of 2000. Parts 2–6 define extensions to both the compression technology and the file format and are currently in various stages of development. In this paper, a technical description of Part 1 of the JPEG 2000 standard is provided, and the rationale behind the selected technologies is explained. Although the JPEG 2000 standard only specifies the decoder and the codesteam syntax, the discussion will span both encoder and decoder issues to provide a better understanding of the standard in various applications.

528 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202361
2022179
2021215
2020168
2019196
2018158